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swin-tiny-patch4-window7-224-mulder-v-scully-colab2

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5344
  • Accuracy: 1.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 1 0.6899 0.5
No log 2.0 2 0.6701 0.25
No log 3.0 3 0.6309 0.5
No log 4.0 4 0.6049 0.5
No log 5.0 5 0.5828 0.5
No log 6.0 6 0.5650 0.75
No log 7.0 7 0.5486 0.75
No log 8.0 8 0.5344 1.0
No log 9.0 9 0.5240 1.0
0.2978 10.0 10 0.5149 1.0
0.2978 11.0 11 0.5066 1.0
0.2978 12.0 12 0.4980 1.0
0.2978 13.0 13 0.4880 1.0
0.2978 14.0 14 0.4699 1.0
0.2978 15.0 15 0.4507 1.0
0.2978 16.0 16 0.4310 1.0
0.2978 17.0 17 0.4155 1.0
0.2978 18.0 18 0.4054 1.0
0.2978 19.0 19 0.3994 1.0
0.1751 20.0 20 0.3970 1.0

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Evaluation results